Topic: "control-variates"
agadetsky/pytorch-pl-variance-reduction
Low-variance Black-box Gradient Estimates for the Plackett-Luce Distribution, AAAI 2020 and NeurIPS 2019 Bayesian Deep Learning Workshop
Language: Jupyter Notebook - Size: 410 KB - Last synced at: almost 2 years ago - Pushed at: over 4 years ago - Stars: 35 - Forks: 2
VITA-Group/SteinDreamer
“SteinDreamer: Variance Reduction for Text-to-3D Score Distillation via Stein Identity” by Peihao Wang, Zhiwen Fan, Dejia Xu, Dilin Wang, Sreyas Mohan, Forrest Iandola, Rakesh Ranjan, Yilei Li, Qiang Liu, Zhangyang Wang, Vikas Chandra
Size: 163 MB - Last synced at: about 2 months ago - Pushed at: over 1 year ago - Stars: 34 - Forks: 1
mcrescas/viltrum-mitsuba
This repository contains the source code of the paper Primary-Space Adaptive Control Variates using Piecewise-Polynomial Approximations by Miguel Crespo, Adrian Jarabo, and Adolfo Muñoz from ACM Transactions on Graphics.
Language: C++ - Size: 54.9 MB - Last synced at: 29 days ago - Pushed at: about 3 years ago - Stars: 21 - Forks: 5
adolfomunoz/viltrum
VILTRUM: Varied Integration Layouts for arbiTRary integrals in a Unified Manner - A C++17 header-only library that provides a set of numerical integration routines
Language: C++ - Size: 383 KB - Last synced at: 20 days ago - Pushed at: 3 months ago - Stars: 16 - Forks: 4
msabvid/Deep-PDE-Solvers
Unbiased Deep Learning based Solvers for parametric PDEs
Language: Python - Size: 1.95 MB - Last synced at: over 1 year ago - Pushed at: over 3 years ago - Stars: 9 - Forks: 6
lehduong/Job-Scheduling-with-Reinforcement-Learning
Learning in Noisy MDP (which is governed by stochastic, exogenous input processes) with input-dependent baseline
Language: Python - Size: 554 KB - Last synced at: about 2 years ago - Pushed at: over 4 years ago - Stars: 6 - Forks: 0
wmkouw/ctrl-iwxval
Controlled importance-weighted cross-validation
Language: MATLAB - Size: 344 KB - Last synced at: 24 days ago - Pushed at: over 5 years ago - Stars: 6 - Forks: 0
juliusberner/robust_kolmogorov
Robust SDE-Based Variational Formulations for Solving Linear PDEs via Deep Learning (ICML 2022)
Language: Python - Size: 108 KB - Last synced at: about 2 years ago - Pushed at: over 2 years ago - Stars: 2 - Forks: 1
anthonyli01/Advanced-Simulation-Methods
This project focuses on applying advanced simulation methods for derivatives pricing. It includes Monte-Carlo, Variance Reduction Techniques, Distribution Sampling Methods, Euler Schemes, and Milstein Schemes.
Language: Jupyter Notebook - Size: 1.44 MB - Last synced at: 10 months ago - Pushed at: 10 months ago - Stars: 1 - Forks: 2
andreagrbic/master_rad_matf
Vrednovanje azijskih opcija
Language: R - Size: 739 KB - Last synced at: about 1 year ago - Pushed at: about 1 year ago - Stars: 1 - Forks: 0
kgourgou/cupac_cuped_control_variates
Implementation of CUPED/CUPAC
Language: Jupyter Notebook - Size: 5.86 KB - Last synced at: 8 days ago - Pushed at: over 2 years ago - Stars: 1 - Forks: 0
lx10077/rlpy
A pytorch-version implementation of RL algorithms. Now it collects TRPO, ClipPPO, A2C, GAIL and ADCV.
Language: Python - Size: 4.11 MB - Last synced at: almost 2 years ago - Pushed at: over 5 years ago - Stars: 1 - Forks: 1
anthonyli01/R-Derivatives-Pricing
University Project: simulation techniques to price derivatives. It will involve Monte-Carlo, variance-reduction techniques, and advanced simulation methods.
Size: 1.38 MB - Last synced at: over 1 year ago - Pushed at: over 2 years ago - Stars: 0 - Forks: 0
sverdoot/control-variates
Project on using control variates for bayesian neural networks
Language: Jupyter Notebook - Size: 55.8 MB - Last synced at: 5 months ago - Pushed at: over 4 years ago - Stars: 0 - Forks: 0
